Image processing apparatus, image processing method, and program

ABSTRACT

An image processing apparatus  100  is provided with a converter  102  to convert a first color image into lightness information and color information other than the lightness information, a lightness compressor  104  to generate compressed lightness information obtained by decimating a pixel value from the lightness information, a reconverter  106  to combine the compressed lightness information and the color information to generate a second color image, an edge extractor  108  to extract an edge included in the first color image, and a pixel value changer  110  to change a pixel value at a position of the edge in the second color image while maintaining similar colors, to generate a third color image.

TECHNICAL FIELD

The present disclosure relates to an image processing technique forcolor image processing.

BACKGROUND ART

Image processing to convert a photograph into an illustration-like imageis known. In such image processing for illustration, a process forcoloring an edge in black is performed. Or a filtering process toemphasize the edge is performed (see, Japanese Patent Laid-OpenPublication No. 2001-24872 and Japanese Patent No. 3689754).

DISCLOSURE OF INVENTION

However, when an edge is merely colored in black, it may be apparentthat an image is automatically generated by CG (Computer Graphics).Moreover, in the filtering process to emphasize an edge, an edge in asubject image is emphasized, so that the subject image becomesunnatural.

The present disclosure is made under consideration of the above pointsto provide an image processing apparatus, an image processing method,and a program, capable of generating an illustration-like image which ismore natural as if drawn by a human being.

According to an aspect of the present disclosure, there is provided animage processing apparatus comprising: a converter to convert a firstcolor image into lightness information and color information other thanthe lightness information;

a lightness compressor to generate compressed lightness informationobtained by decimating a pixel value from the lightness information;

a reconverter to combine the compressed lightness information and thecolor information to generate a second color image;

an edge extractor to extract an edge included in the first color image;and

a pixel value changer to change a pixel value at a position of the edgein the second color image while maintaining similar colors, to generatea third color image.

The pixel value changer may change the pixel value at the position ofthe edge in the second color image, while maintaining the similarcolors, to a pixel value of a darker tone when luminance in an innerarea of the edge in the second color image is higher than luminance inan outer area of the edge.

The pixel value changer may change the pixel value at the position ofthe edge in the second color image to a value obtained by multiplyingthe pixel value by a predetermined coefficient.

The edge extractor may further comprise:

a monochrome converter to convert the first color image into amonochrome image;

a blur processor to generate a blurred image obtained by blurring themonochrome image;

a ratio detector to detect a ratio of a pixel value of the blurred imageand a pixel value of the monochrome image, the pixel value of themonochrome image corresponding to the pixel value of the blurred image;

a ratio determiner to determine whether the ratio is larger than apredetermined threshold value; and

an edge output unit to output a pixel having the ratio determined asbeing larger than the predetermined threshold value, as an edge in themonochrome image.

The blur processor may generate the blurred image by a filtering processto the monochrome image using a Gaussian filter having a filter size inaccordance with an outer size of the monochrome image.

The blur processor may generate the blurred image by a filtering processto the monochrome image using a Gaussian filter having a filter size inaccordance with an outer size of the third color image. The outer sizeof the third color image may be an output size of a printer to print thethird color image on a print paper.

According to an aspect of the present disclosure, there is provided animage processing apparatus comprising:

a blur processor to generate a blurred image obtained by blurring amonochrome image;

a ratio detector to detect a ratio of a pixel value of the blurred imageand a pixel value of the monochrome image, the pixel value of themonochrome image corresponding to the pixel value of the blurred image;

a ratio determiner to determine whether the ratio is larger than apredetermined threshold value; and

an edge output unit to output a pixel having the ratio determined asbeing larger than the predetermined threshold value, as an edge in themonochrome image.

According to an aspect of the present disclosure, there is provided animage processing method comprising:

converting a first color image into lightness information and colorinformation other than the lightness information;

generating compressed lightness information obtained by decimating apixel value from the lightness information;

combining the compressed lightness information and the color informationto generate a second color image;

extracting an edge included in the first color image; and

changing a pixel value at a position of the edge in the second colorimage while maintaining similar colors, to generate a third color image.

According to an aspect of the present disclosure, there is provided animage processing method comprising:

generating a blurred image obtained by blurring a monochrome image;

detecting a ratio of a pixel value of the blurred image and a pixelvalue of the monochrome image, the pixel value of the monochrome imagecorresponding to the pixel value of the blurred image;

determining whether the ratio is larger than a predetermined thresholdvalue; and

outputting a pixel having the ratio determined as being larger than thepredetermined threshold value, as an edge in the monochrome image.

According to an aspect of the present disclosure, there is provided acomputer readable program to be executed by a computer, comprising:

converting a first color image into lightness information and colorinformation other than the lightness information;

generating compressed lightness information obtained by decimating apixel value from the lightness information;

combining the compressed lightness information and the color informationto generate a second color image;

extracting an edge included in the first color image; and

changing a pixel value at a position of the edge in the second colorimage while maintaining similar colors, to generate a third color image.

According to an aspect of the present disclosure, there is provided acomputer readable program to be executed by a computer, comprising:

generating a blurred image obtained by blurring a monochrome image;

detecting a ratio of a pixel value of the blurred image and a pixelvalue of the monochrome image, the pixel value of the monochrome imagebeing corresponding to the pixel value of the blurred image;

determining whether the ratio is larger than a predetermined thresholdvalue; and

extracting a pixel having the ratio determined as being larger than thepredetermined threshold value, as an edge in the monochrome image.

According to the present disclosure, an illustration-like image which ismore natural as if drawn by a human being can be generated.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram showing a configuration of an image processingsystem according to a first embodiment;

FIG. 2 is a block diagram showing a configuration of an edge extractor;

FIG. 3 is a diagram showing coefficients in a filter size of [5×5];

FIG. 4 is a diagram showing a flowchart of an illustration process in animage processing apparatus;

FIG. 5 is a view showing images related to an edge extraction process;

FIG. 6 is a view showing images related to a decimation process; and

FIG. 7 is a diagram showing a flowchart of an illustration process in asecond embodiment.

BEST MODE FOR CARRYING OUT THE INVENTION

Hereinbelow, embodiments in the present disclosure will be explainedwith reference to the drawings.

First Embodiment

An image processing apparatus according to a first embodiment is toobtain an illustration-like image which seems to be more natural bychanging a pixel value at the position of an edge of a color image to apixel value of a darker tone while maintaining similar colors, based onthe position of an extracted edge. The image processing apparatus willbe explained hereinbelow in more detail.

FIG. 1 is a diagram showing a configuration of an image processingsystem 1 according to the first embodiment. The image processing system1 of FIG. 1 can, for example, be built in various types of electronicequipment (such as a personal computer) having a built-in CPU (CentralProcessing Unit). More specifically, the CPU executes a dedicatedprogram to perform an operation of the image processing system 1 ofFIG. 1. Or dedicated hardware equipment to perform the operation of theimage processing system 1 of FIG. 1 may be provided.

The image processing system 1 of FIG. 1 is provided with a storagedevice 10, a controller 12, a camera 14, an input device 16, a displaydevice 18, a printer 20, and an image processing apparatus 100. Thestorage device 10 stores, in addition to a system program, various typesof processing programs such as a face-image photographing processingprogram and an image processing program, and data or the like processedby each program. The controller 12 has a CPU, a RAM (Random AccessMemory), etc., to read out various types of programs such as the systemprogram and the image processing program stored in the storage device 10and to develop the programs in the RAM for centralized control on theoperation of each component in accordance with the programs.

The camera 14 has an optical lens, an optical sensor such as a CCD(Charge Coupled Device), an A/D (Analog/Digital) converter, etc., toconvert a subject image, which is input through the optical lens inphotographing, by photoelectric conversion by the optical sensor, togenerate an analog image signal. The A/D converter converts the analogimage signal into a digital first color image and supplies the firstcolor image to the controller 12. One pixel of the first color image,which is a natural image, is expressed by a gradation signal of threeprimary colors of R (red), G (green) and B (blue), for example. In moredetail, RGB elements of one pixel are each expressed by an 8-bitgradation signal. Therefore, one pixel of the first color image iscomposed of 24 bits (8 bits×3 colors). The number of bits of one pixelis not limited to the above-described value. The color components thatconstitute one pixel are not limited to the RGB three colors. Forexample, yellow or white color pixels, or color pixels of RGBcomplementary colors may be provided.

The input device 16 has a touch panel integrally built in a panel of thedisplay device 18, various types of function keys, such as, aphotograph-type selection switch (hereinafter, SW) for selecting aphotograph type, a photographing SW for instructing the start ofphotographing, a print SW for instructing the production ofphotographed-image print output, and so on. The input device 16 outputsan operation signal corresponding to an operated key to the controller12.

The display device 18 has, for example, an LCD (Liquid Crystal Display)to display a guidance screen for explaining a photographing procedure,various types of operation screens such as a selection screen forselecting a photograph type, a subject image photographed by the camera14, an illustration-like image processed by the image processingapparatus 100, and so on, in accordance with a control signal from thecontroller 12.

The printer 20 produces print output based on an image input from thecontroller 12. A printing method applicable to the printer 20 is, forexample, a sublimation transfer method to sublimate and transfer acoloring material to form an image. Another applicable printing methodis a thermal fusion transfer recording method to superpose a recordingmedium and an image receiving material on each other and heat them totransfer a recording layer of the recording medium onto an imagereceiving layer of the image receiving material to form an image.Electrophotography, an ink jet method, and other printing methods arealso applicable. Moreover, a silver halide photo image may be formed.

The image processing apparatus 100 performs image processing to processan input first color image into an illustration-like image. The imageprocessing apparatus 100 is provided with a converter 102, a lightnesscompressor 104, a reconverter 106, an edge extractor 108, and a pixelvalue changer 110.

The converter 102 converts the first color image input from thecontroller 12 into lightness information and color information otherthan the lightness information. The lightness information is a valueindicating a scale of color image brightness. For example, the converter102 converts an RGB first color image into YCbCr image data. Luminance(lightness) Y which expresses the lightness information can becalculated using, for example, a conversion formulaY=0.29900×R+0.58700×G+0.11400×B. In this way, lightness information perpixel is generated using the first color image.

Moreover, the converter 102 converts the RGB first color image intocolor information Cb, other than the lightness information, using, forexample, a conversion formula Cb=−0.16874×R−0.33126×G+0.50000×B.Likewise, the converter 102 converts the RGB first color image intocolor information Cr, other than the lightness information, using, forexample, a conversion formula Cr=0.50000×R−0.41869×G−0.0081×B. The colorinformation Cb, which is also referred to as color differenceinformation, indicates hue and colorfulness in a blue color system. Thecolor information Cr, which is also referred to as color differenceinformation, indicates hue and colorfulness in a red color system.Accordingly, using the first color image, the color information Cb andCr per pixel are generated.

The converter 102 may generate the lightness information and the colorinformation, using a method other than the method for converting the RGBfirst color image into YCbCr. For example, the first color image may beconverted into a Lab or HLS color system.

The lightness compressor 104 generates compressed lightness informationby decimating the lightness information obtained by the converter 102.Even if the first color image originally has information of linearbrightness, the first color image is converted to have brightness offive stages.

More specifically, for example, when lightness information per pixelobtained by the converter 102 is in a range of (0 to 100), the lightnessinformation is converted into compressed lightness information (100)after decimation of pixel values having lightness information in a rangeof (100 to 95). Likewise, the lightness information is converted intocompressed lightness information (80) after decimation of pixel valueshaving lightness information in a range of (95 to 55). Likewise, thelightness information is converted into compressed lightness information(60) after decimation of pixel values having lightness information in arange of (55 to 30), into compressed lightness information (25) afterdecimation of pixel values having lightness information in a range of(33 to 10), and into compressed lightness information (0) afterdecimation of pixel values having lightness information in a range of(10 to 0). By performing a decimation process described above,conversion is performed to have a lightness-compressed image having aclear difference in brightness entirely. Compressed lightnessinformation Y′ in the above is equivalent to a pixel value per pixel ina lightness-compressed image obtained by decimating luminance of aluminance image.

The reconverter 106 combines the compressed lightness informationobtained by the lightness compressor 104 and the color information otherthan the lightness information obtained by the converter 102 to generatea second color image.

More specifically, the reconverter 106 uses the compressed lightnessinformation Y′ obtained by the lightness compressor 104 and the colorinformation Cb and Cr obtained by the converter 102 to generate thesecond color image. The second color image having the lightnessinformation decimated in this way is converted into an image havingillustration-like lightness with a clear difference in brightnessentirely.

The edge extractor 108 extracts an edge included in the first colorimage. A configuration of the edge extractor 108 will be described laterin detail.

The pixel value changer 110 changes a pixel value at the position of anedge in the second color image while maintaining similar colors togenerate a third color image (an illustration-like image). Morespecifically, in the second color image, when the lightness in an innerarea of the edge in the second image is higher than the lightness in anouter area of the edge, the pixel value changer 110 changes the pixelvalue at the position of the edge in the second color image, whilemaintaining similar colors, to a pixel value of a darker tone.

For example, the pixel value changer 110 changes the pixel value at theposition of the edge in the second color image to a value obtained bymultiplying the pixel value by a predetermined coefficient. Morespecifically, the pixel value changer 110 converts the pixel value atthe position of the edge obtained by the edge extractor 108 by ½ or ¼times to deepen the edge color. In this case, RGB gradation values perpixel are changed to values obtained by multiplying the RGB gradationvalues per pixel by a predetermined coefficient (for example, ½ or ¼).

In the manner described above, having the edge's original tone beingmaintained, the original tone is more deepened. For example, when theoriginal color is pink, an edge with deepened pink is generated. Forexample, when the original color is green, an edge with deepened greenis generated. In this way, by generating an edge while maintaining theoriginal color, an image viewed as if painted with paint can beobtained. In other words, an illustration-like image, which is hardlyrecognized as a CG-generated image, can be obtained. When the pixelvalue changer 110 deepens the edge color, the coefficient value to bemultiplied to the RGB gradation values per pixel may be changed for eachof the RGB components.

Subsequently, a configuration of the edge extractor 108 will beexplained in detail based on FIG. 2. FIG. 2 is a block diagram showingthe configuration of the edge extractor 108. As shown in FIG. 2, theedge extractor 108 is provided with a monochrome converter 112, a blurprocesser 114, a ratio detector 116, a ratio determiner 118, and an edgeoutput unit 120.

The monochrome converter 112 converts the first color image into amonochrome image. The monochrome converter 112 converts the RGB firstcolor image into luminance (lightness)-Y information in accordance withthe above-described conversion formula. The monochrome image isequivalent to the luminance information.

The blur processer 114 generates a blurred image by blurring themonochrome image. More specifically, for example, the blur processer 114applies a filtering process to the monochrome image to generate ablurred image, using a Gaussian filter having a filter size inaccordance with the outer size of the monochrome image.

The ratio detector 116 detects a ratio of a pixel value of the blurredimage obtained by the blur processer 114 and a pixel value of themonochrome image, which corresponds to the pixel value of the blurredimage. More specifically, the ratio detector 116 calculates the ratiousing an expression Ratio=Blurred-image pixel value/Monochrome-imagepixel value. The ratio determiner 118 determiners whether the calculatedratio is larger than a predetermined threshold value.

The edge output unit 120 outputs a pixel, for which the ratio detectedby the ratio detector 116 is determined as being larger than thepredetermined threshold value, as an edge in the monochrome image. Forexample, when outputting, as an edge, an area having a ratio of 0.9 orhigher, an edge, for which the luminance of an inner area of the edge ishigher than the luminance of an outer area of the edge, can be detected.Accordingly, for example, for an image of a human being, an edge can beset at an outer portion along the contour of a human face. There is nopossibility of extracting an edge that cuts into the face. Therefore,there is no problem in that impression of the human face changes due tounnatural edge extraction.

As the Gaussian filter used by the blur processer 114 has a largerfilter size, the edge output unit 120 can output a smaller (weaker)edge. On the other hand, as the Gaussian filter has a smaller filtersize, the edge output unit 120 cannot extract a smaller edge. A small(weak) edge is a contour line with a relatively moderate change inluminance. A large (strong) edge is a contour line with a drastic changein luminance.

An image with a small area becomes complicated when even a small edge isextracted, and hence it is desirable to extract a large edge only. Onthe other hand, for an image with a large area, image reproducibilitybecomes excellent by extracting even a small edge. For this reason, inthe present embodiment, the filter size is changed according to a shortside size of image data. In detail, as the image data has a longer shortside, the Gaussian filter of the blur processer 114 is changed to have alarger filter size.

As described above, by changing the filter size of the Gaussian filterused in the blur processer 114, the size of an edge to be extracted ischanged. Moreover, by changing the filter size of the Gaussian filter,the width of an edge output by the edge output unit 120 is changed.Specifically, as the filter size becomes larger, the edge output by theedge output unit 120 has a larger width.

As described above, in the monochrome image, a portion with a drasticchange in luminance becomes a large (strong) edge whereas a portion witha moderate change in luminance becomes a small (weak) edge. Therefore,when the strong and weak edges are compared to each other, for thestrong edge, a differential value between the corresponding pixel valuesof the blurred image obtained by the blur processer 114 and of themonochrome image becomes large. As the differential value becomeslarger, the edge output unit 120 outputs an edge with a larger width.Accordingly, the strong edge has a larger width than the weak edge. Inthis way, the strong edge with a drastic change in luminance has a thickline whereas the weak edge with a moderate change in luminance has anarrow line, with the edge width continuously changing in accordancewith the luminance difference. As described above, in the presentembodiment, since the contour line thickness is changeable in accordancewith the edge strength, an image shown as if painted with paint can beobtained.

Subsequently, coefficients of the Gaussian filter in the blur processer114 will be explained based on FIG. 3. FIG. 3 is a diagram showingcoefficients in a filter size of [5×5]. As shown in FIG. 3, acoefficient f (x, y) is calculated in accordance with the Gaussiandistribution function expressed by the following expression (1).

$\begin{matrix}{{f( {x,y} )} = {\frac{1}{2\; {\pi\sigma}^{2}}{\exp ( {- \frac{x^{2} + y^{2}}{2\sigma^{2}}} )}}} & {{Expression}\mspace{14mu} (1)}\end{matrix}$

Here, (x, y) indicates a distance from a target pixel. In practice,coefficients are normalized so that the sum of all coefficientsbecomes 1. More specifically, the coefficients are normalized inaccordance with an expression (2).

$\begin{matrix}{{f^{\prime}( {x,y} )} = \frac{f( {x,y} )}{\sum_{k,l}{f( {k,l} )}}} & {{Expression}\mspace{14mu} (2)}\end{matrix}$

A filter size [N×N] is calculated using the value of a vertical ortransversal short side of an input image. More specifically, the filtersize [N×N] is calculated using an expression Filter one-sidelength=Short side length/Defined value. The short side length is thelength of a shorter side between a vertical side of and a transversalside of the input image. Therefore, the filter size [N×N] is calculatedwith N=Filter one-side length/Pixel size.

Subsequently, a flow of an illustration process will be explained basedon FIGS. 4 to 6. FIG. 4 is a diagram showing a flowchart of theillustration process in the image processing apparatus 100. Withreference to FIG. 4, an example of an edge extraction process and alightness decimation process performed in parallel, will be explained.Either of the processes may, however, be performed before the other ofthe processes.

FIG. 5 is a view showing images related to the edge extraction process.FIG. 5(a) is a first color image of a rose photographed by the camera14. FIG. 5(b) is a monochrome image converted by the monochromeconverter 112. FIG. 5(c) is a blurred image obtained by the blurprocesser 114. FIG. 5(d) is an image with an edge, obtained by the edgeoutput unit 120, shown in black.

FIG. 6 is a view showing images related to the decimation process. FIG.6(a) is the first color image of the rose photographed by the camera 14.FIG. 6(b) is an image (luminance image) indicating lightness informationconverted by the converter 102. FIG. 6(c) is an image (compressedlightness image) indicating compressed lightness information obtained bythe lightness compressor 104. FIG. 6(d) is a second color image obtainedby the reconverter 106. FIG. 6(e) is a third color image obtained by thepixel value changer 110.

First of all, a flow of the edge extraction process will be explained.As shown in FIG. 4, the first color image (FIGS. 5(a) and 6(a)) of therose photographed by the camera 14 is input to the monochrome converter112 and the converter 102 via the controller 12 (step S500).

Subsequently, the monochrome converter 112 converts the first colorimage to the monochrome image (FIG. 5(b)) in accordance with theabove-described conversion formula (step S502). In this way, the firstcolor image is converted into a monochrome image having lightness Y from0 to 100.

Subsequently, the blur processer 114 calculates a filter size based on ashort side length of the monochrome image to calculate coefficients ofthe Gaussian distribution function, and then performs a filteringprocess to all pixels of the monochrome image, to generate a blurredimage (FIG. 5(c)) (step S504).

Subsequently, the ratio detector 116 detects a ratio of a pixel value ofthe blurred image and a pixel value of the monochrome image, whichcorresponds to the pixel value of the blurred image (step S506). Then,the edge output unit 120 outputs a pixel for which the ratio isdetermined as larger than a predetermined threshold value, as an edge inthe monochrome image (step S508). Here, a pixel for which the ratio isequal to or higher than 0.7 but lower than 1.0 is output as the edge. Inthis case, pixels corresponding to the edge, defined as having a pixelvalue of 0 (corresponding to black in FIG. 5(d)), and the other pixelsdefined as having a pixel value of 100 (corresponding to white in FIG.5(d)) are output.

Subsequently, a flow of the decimation process will be explained. Asshown in FIG. 4, the converter 102 converts the first color image (FIG.6(a)) input from the controller 12 into lightness information (FIG.6(b)) Y and color information other than the lightness information (stepS602).

Subsequently, the lightness compressor 104 generates compressedlightness information Y′ obtained by decimating the lightnessinformation Y (step S604). Here, lightness information Y (FIG. 6(b))having a value in the range of 0 to 100 is decimated to generatecompressed lightness information Y′ having a value of any of 100, 80,60, 25, and 0 (FIG. 6(c)).

Subsequently, the reconverter 106 combines the compressed lightnessinformation Y′ obtained by the lightness compressor 104 and the colorinformation Cb and Cr obtained by the converter 102 to generate a secondcolor image (FIG. 6(d)) (step S606), the information being reconvertedinto a second color image having RGB gradation values for each onepixel.

Subsequently, the pixel value changer 110 changes a pixel value at theposition of an edge in the second color image while maintaining similarcolors to generate a third color image (FIG. 6(e)) (step S608). Here, avalue of each of RGB components corresponding to the position of theedge output by the edge output unit 120 is multiplied by ½. In otherwords, a value of each of RGB gradation values of the second color imagecorresponding to the position (a pixel indicating a pixel value of 100)of the edge output by the edge output unit 120 is multiplied by ½.Subsequently, the pixel value changer 110 outputs the third color imageto the display device 18 and the printer 20 via the controller 12, andthe entire process ends.

As described above, in the edge extraction process, by detecting theratio of a pixel value of a blurred image and a pixel value of amonochrome image, which corresponds to the pixel value of the blurredimage, it is possible to output a strong edge having a larger width.Moreover, in the lightness decimation process, by generating compressedlightness information having lightness information decimated after theconversion of a first color image into the lightness information, and byreconverting the compressed lightness information into a second colorimage, it is possible to obtain a second color image with a cleardifference in brightness entirely. Moreover, by making thick the edgecolor of the second color image, it is possible to obtain a third colorimage (illustration-like image) which is shown as if painted with paint.In this case, for a stronger edge, by making the edge thicker, it ispossible to obtain an illustration-like image which seems to be morenatural.

As described above, according to the first embodiment, since a pixelvalue at the position of an extracted edge is changed while maintainingsimilar colors, an illustration-like image, which seems to be morenatural as if painted with paint, can be generated. Moreover, since theedge width is variable depending on whether the edge is strong or weak,the edge width can be optimized in accordance with the surroundingimages, and hence an image with no strange impression can be obtained.

Second Embodiment

In the above-described first embodiment, the blur processer 114 sets thefilter size in accordance with the outer size of a monochrome image.Another condition may be considered for setting the filter size. Adifferent condition for setting the filter size is, for example, theouter size of the third color image that is an output result of theprinter 20. Hereinbelow, the portion different from the first embodimentwill be explained. The configuration of the image processing system 1 isthe same as that shown in FIGS. 1 to 3, hence the explanation thereofbeing omitted.

FIG. 7 is a diagram showing a flowchart of an illustration process in asecond embodiment. The image processing apparatus according to thesecond embodiment has the same configuration as that of FIG. 1, exceptfor the illustration process different from the first embodiment. InFIG. 7, the same process as that of FIG. 4 is given the same stepnumber. Hereinbelow, the different points will mainly be explained. Asshown in FIG. 7, when starting the illustration process, the controller12 acquires an image output size set in the printer 20 and outputs theimage output size to the blur processer 114 (step S701).

The blur processer 114 blurs a monochrome image to generate a blurredimage based on the Gaussian filter having a filter size set inaccordance with a short side length of the image output size set in theprinter 20 (step S704). As described, the blur processer 114 sets thefilter size of the Gaussian filter in accordance with the outer size ofthe above-described third color image.

Subsequently, the pixel value changer 110 further changes the size ofthe third color image generated by the pixel value changer 110 to theouter size of the third color image, that is, the output size of theprinter 20, and outputs the changed size to the display device 18 andthe printer 20 via the controller 12 (step S710), and the entire processends.

As described above, in the second embodiment, since the filter size isset in accordance with the outer size of the third color image, that is,the output size of the printer 20, an edge having a size and width fitto the outer size of the third color image can be generated.Accordingly, even when the outer size of the third color image changesvariously, an illustration-like image shown as if actually drawn by ahuman being can be generated.

As described above, according to the second embodiment, since the filtersize is set in accordance with the outer size of the third color imagegenerated by the pixel value changer 110, that is, the output size ofthe printer 20, edge extraction optimum to the outer size of the thirdcolor image can be performed.

In the above-described first and second embodiments, the Gaussian filteris used for the blurring process. However, the filter to be used for theblurring process may not necessary be the Gaussian filter, for example,the Laplacian filter may be used. However, in the first and secondembodiments, not directly extracting an edge with the filter, but thefilter is used for the blurring process. Therefore, there is nolimitation on the actual filter type, as far as a filter to be used iscapable of the blurring process and is filter-size changeable.

At least part of the image processing apparatus 100 explained in theabove-described embodiments may be configured with hardware or software.When it is configured with software, a program that performs at leastpart of the image processing apparatus 100 may be stored in a storagemedium such as a flexible disk and CD-ROM, and then installed in acomputer to run thereon. The storage medium may not be limited to adetachable one such as a magnetic disk and an optical disk but may be astandalone type such as a hard disk and a memory.

Moreover, a program that achieves the function of at least part of theimage processing apparatus 100 may be distributed via a communicationnetwork a (including wireless communication) such as the Internet. Theprogram may also be distributed via an online network such as theInternet or a wireless network, or stored in a storage medium anddistributed under the condition that the program is encrypted, modulatedor compressed.

The present disclosure is not limited to the embodiments described abovebut includes various modifications conceivable by those skilled in theart. The effects of the present disclosure are also not limited to thosedescribed above. Namely, various additions, modifications and partialomissions may be made without departing from the conceptual idea andgist of present disclosure derived from those defined in theaccompanying claims and their equivalents.

1. An image processing apparatus comprising: a converter to convert afirst color image into lightness information and color information otherthan the lightness information; a lightness compressor to generatecompressed lightness information obtained by decimating a pixel valuefrom the lightness information; a reconverter to combine the compressedlightness information and the color information to generate a secondcolor image; an edge extractor to extract an edge included in the firstcolor image; and a pixel value changer to change a pixel value at aposition of the edge in the second color image while maintaining similarcolors, to generate a third color image.
 2. The image processingapparatus of claim 1, wherein the pixel value changer changes the pixelvalue at the position of the edge in the second color image, whilemaintaining the similar colors, to a pixel value of a darker tone whenluminance in an inner area of the edge in the second color image ishigher than luminance in an outer area of the edge.
 3. The imageprocessing apparatus of claim 1, wherein the pixel value changer changesthe pixel value at the position of the edge in the second color image toa value obtained by multiplying the pixel value by a predeterminedcoefficient.
 4. The image processing apparatus of claim 1, wherein theedge extractor further comprises: a monochrome converter to convert thefirst color image into a monochrome image; a blur processor to generatea blurred image obtained by blurring the monochrome image; a ratiodetector to detect a ratio of a pixel value of the blurred image and apixel value of the monochrome image, the pixel value of the monochromeimage corresponding to the pixel value of the blurred image; a ratiodeterminer to determine whether the ratio is larger than a predeterminedthreshold value; and an edge output unit to output a pixel having theratio determined as being larger than the predetermined threshold value,as an edge in the monochrome image.
 5. The image processing apparatus ofclaim 4, wherein the blur processor generates the blurred image by afiltering process to the monochrome image using a Gaussian filter havinga filter size in accordance with an outer size of the monochrome image.6. The image processing apparatus of claim 4, wherein the blur processorgenerates the blurred image by a filtering process to the monochromeimage using a Gaussian filter having a filter size in accordance with anouter size of the third color image.
 7. The image processing apparatusof claim 6, wherein the outer size of the third color image is an outputsize of a printer to print the third color image on a print paper. 8.(canceled)
 9. An image processing method comprising: converting a firstcolor image into lightness information and color information other thanthe lightness information; generating compressed lightness informationobtained by decimating a pixel value from the lightness information;combining the compressed lightness information and the color informationto generate a second color image; extracting an edge included in thefirst color image; and changing a pixel value at a position of the edgein the second color image while maintaining similar colors, to generatea third color image.
 10. (canceled)
 11. A recording medium that stores aprogram, the program that causes a computer to execute: converting afirst color image into lightness information and color information otherthan the lightness information; generating compressed lightnessinformation obtained by decimating a pixel value from the lightnessinformation; combining the compressed lightness information and thecolor information to generate a second color image; extracting an edgeincluded in the first color image; and changing a pixel value at aposition of the edge in the second color image while maintaining similarcolors, to generate a third color image.
 12. (canceled)